code: def from_embeddings(cls, embeddings: np.ndarray) -> "VectorIndex":
      index = faiss.IndexFlatL2(embeddings.shape[1])
      index.add(embeddings)
      return cls(index)
  
file_path: ludwig/ludwig/vector_index/faiss.py
imports: import faiss
  import numpy
  from ludwig.vector_index.base import VectorIndex
label_desc: Use image node_id 5 for calling the FaissIndex obj's underlying member method code with example usage: obj.from_embeddings(cls, embeddings) and returns: cls